Multivariate dynamic model for ordinal outcomes

Individual or stand-level biomass is not easy to measure. The current methods employed, based on cutting down a representative sample of plantations, make it possible to assess the biomasses for various compartments (bark, dead branches, leaves, . . .). However, this felling makes individual longitudinal follow-up impossible. In this context, we propose a method to evaluate individual biomasses by compartments when these biomasses are taken as ordinals. Biomass is measured visually and observations are therefore not destructive. The technique is based on a probit model redefined in terms of latent variables. A generalization of the univariate case to the multivariate case is then natural and takes into account the dependency between compartment biomasses. These models are then extended to the longitudinal case by developing a Dynamic Multivariate Ordinal Probit Model. The performance of the MCMC algorithm used for the estimation is illustrated by means of simulations built from known biomass models. The quality of the estimates and the impact of certain parameters, are then discussed

Conventional analysis methods underestimate the plant-available pools of calcium, magnesium and potassium in forest soils

The plant-available pools of calcium, magnesium and potassium are assumed to be stored in the soil as exchangeable cations adsorbed on the cation exchange complex. In numerous forest ecosystems, despite very low plant-available pools, elevated forest productivities are sustained. We hypothesize that trees access nutrient sources in the soil that are currently unaccounted by conventional soil analysis methods. We carried out an isotopic dilution assay to quantify the plant-available pools of calcium, magnesium and potassium and trace the soil phases that support these pools in 143 individual soil samples covering 3 climatic zones and 5 different soil types. For 81%, 87% and 90% of the soil samples (respectively for Ca, Mg and K), the plant-available pools measured by isotopic dilution were greater than the conventional exchangeable pool. This additional pool is most likely supported by secondary non-crystalline mineral phases in interaction with soil organic matter and represents in many cases (respectively 43%, 27% and 47% of the soil samples) a substantial amount of plant-available nutrient cations (50% greater than the conventional exchangeable pools) that is likely to play an essential role in the biogeochemical functioning of forest ecosystems, in particular when the resources of Ca, Mg and K are low

Modeling soil organic carbon dynamics in temperate forests with Yasso07

In a context of global changes, modeling and predicting the dynamics of soil carbon stocks (CSs) in forest ecosystems are vital but challenging. Yasso07 is considered to be one of the most promising models for such a purpose. We examine the accuracy of its prediction of soil carbon dynamics over the whole French metropolitan territory at a decennial timescale. We used data from 101 sites in the RENECOFOR network, which encompasses most of the French temperate forests. These data include (i) the quantity of above-ground litterfall from 1994 to 2008, measured yearly, and (ii) the soil CSs measured twice at an interval of approximately 15 years (once in the early 1990s and around 2010). We used Yasso07 to simulate the annual changes in carbon stocks (ACCs; in tC ha−1 yr−1) for each site and then compared the estimates with actual recorded data. We carried out meta-analyses to reveal the variability in litter biochemistry in different tree organs for conifers and broadleaves. We also performed sensitivity analyses to explore Yasso07's sensitivity to annual litter inputs and model initialization settings. At the national level, the simulated ACCs (+0.00±0.07 tC ha−1 yr−1, mean ± SE) were of the same order of magnitude as the observed ones (+0.34±0.06 tC ha−1 yr−1). However, the correlation between predicted and measured ACCs remained weak (R2<0.1). There was significant overestimation for broadleaved stands and underestimation for coniferous sites. Sensitivity analyses showed that the final estimated CS was strongly affected by settings in the model initialization, including litter and soil carbon quantity and quality and also by simulation length. Carbon quality set with the partial steady-state assumption gave a better fit than the model with the complete steady-state assumption. With Yasso07 as the support model, we showed that there is currently a bottleneck in soil carbon modeling and prediction due to a lack of knowledge or data on soil carbon quality and fine-root quantity in the litter

Chemical fertility of forest ecosystems. Part 1: Common soil chemical analyses were poor predictors of stand productivity across a wide range of acidic forest soils

Forest soil fertility can be defined as a combination of physical, chemical and biological factors characterising the biomass production capacity of the soil. However, numerous ecological variables affect tree growth and the aim of the present study was to investigate the specific influence of soil chemical properties on tree productivity at 49 acidic forest sites. A standardized tree productivity index based on tree height expressed as dominant height of the studied stand divided by maximum tree height observed at the same age for the same species in the same climatic region was firstly computed at each site. This index is assumed to limit the influence of species, ages and climate. A soil database was also compiled with data on soil properties from 47 temperate (France) and two tropical (Congo, Brazil) sites. Data included seven tree species, varying in age from 1 to 175 years. Commonly used indicators such as C:N ratio, soil pH, as well as available and total pools of soil nutrients were compared to the standardized tree productivity index, to find the most reliable indicator(s). Nutrient pools at fixed mineral soil depths (down to 100 cm) were used, as well as (for 11 stands) the depth comprising 95% of fine roots. Our results show that none of the common soil chemical parameters tested in this paper could individually explain stand productivity. Combinations of different parameters were also tested using PCA and they could better explain the variability of the data set but without being able to separate the sites according to their standardized tree productivity index. Moreover, random Forests performed on our dataset were unable to properly predict the standardized tree productivity index. Our results reinforce the idea that the influence of the soil chemical fertility on stand productivity is complex and the soil chemical parameters alone (individually or combined) are poor predictors of tree productivity as assessed by the H0:Hmax index. In this paper we focused on static soil chemical indicator and more dynamic indictors, such as nutrient fluxes involved in the biogeochemical cycles, could better explain stand productivity. A companion paper (Legout et al., 2020) focuses on the connection between productivity and different components of the biogeochemical cycle, using data from 11 of the stands presented in this paper

Mycolactone as Analgesic: Subcutaneous Bioavailability Parameters

Mycobacterium ulcerans is the bacillus responsible for Buruli ulcer, an infectious disease and the third most important mycobacterial disease worldwide, after tuberculosis and leprosy. M. ulcerans infection is a type of panniculitis beginning mostly with a nodule or an oedema, which can progress to large ulcerative lesions. The lesions are caused by mycolactone, the polyketide toxin of M. ulcerans. Mycolactone plays a central role for host colonization as it has immunomodulatory and analgesic effects. On one hand, mycolactone induces analgesia by targeting type-2 angiotensin II receptors (AT2R), causing cellular hyperpolarization and neuron desensitization. Indeed, a single subcutaneous injection of mycolactone into the mouse footpad induces a long-lasting hypoesthesia up to 48 h. It was suggested that the long-lasting hypoesthesia may result from the persistence of a significant amount of mycolactone locally following its injection, which could be probably due to its slow elimination from tissues. To verify this hypothesis, we investigated the correlation between hypoesthesia and mycolactone bioavailability directly at the tissue level. Various quantities of mycolactone were then injected in mouse tissue and hypoesthesia was recorded with nociception assays over a period of 48 h. The hypoesthesia was maximal 6 h after the injection of 4 μg mycolactone. The basal state was reached 48 h after injection, which demonstrated the absence of nerve damage. Surprisingly, mycolactone levels decreased strongly during the first hours with a reduction of 70 and 90% after 4 and 10 h, respectively. Also, mycolactone did not diffuse in neighboring skin tissue and only poorly into the bloodstream upon direct injection. Nevertheless, the remaining amount was sufficient to induce hypoesthesia during 24 h. Our results thus demonstrate that intact mycolactone is rapidly eliminated and that very small amounts of mycolactone are sufficient to induce hypoesthesia. Taken together, our study points out that mycolactone ought to be considered as a promising analgesic